Are Tools All We Need? Unveiling the Tool-Use Tax in LLM Agents
University of Houston（休斯顿大学）；University of Southern California（南加州大学）；New York University（纽约大学）；Texas A&M University（德克萨斯农工大学）；University of California, San Diego（加州大学圣地亚哥分校）
Tool-augmented reasoning has become a popular direction for LLM-based agents, and it is widely assumed to improve reasoning and reliability. However, we demonstrate that this consensus does not always hold: in the presence of semantic distractors, tool-augmented reasoning does not necessarily outperform native CoT. To explain this performance gap, we propose a Factorized Intervention Framework that isolates the cost of prompt formatting, the overhead of the tool-calling protocol, and the actual gain from executing tools. Our analysis reveals a critical tradeoff: under semantic noise, the gains from tools often fail to offset the "tool-use tax", which is the performance degradation introduced by the tool-calling protocol itself. To address this, we introduce G-STEP, a lightweight inference-time gate to mitigate protocol-induced errors. While this yields partial recovery, our findings suggest that more substantial improvements still require strengthening the model's intrinsic reasoning and tool-interaction capabilities.
LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络安全学院）；Nanyang Technological University（南洋理工大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Hong Kong University of Science and Technology（香港科技大学）；School of Cyber Science and Engineering, Wuhan University（武汉大学网络安全科学与工程学院）；Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学中关村人工智能学院）；Academy of Mathematics and Systems Science, Chinese Academy of Sciences（中国科学院数学与系统科学研究院）；School of Computing, Faculty of Science and Engineering, Macquarie University（麦考瑞大学计算机学院）；Cyberspace Institute of Advanced Technology, Guangzhou University（广州大学高级技术网络研究所）；Squirrel Ai Learning；Xiaomi Company（小米公司）
Graph-based Agent Memory: Taxonomy, Techniques, and Applications
The Hong Kong Polytechnic University（香港理工大学）；School of Information（信息学院）；Xiamen University（厦门大学）；School of Computing and Information Systems（计算与信息学院）；Singapore Management University（新加坡国立管理学院）；School of Artificial Intelligence（人工智能学院）
LLM Agents in Law: Taxonomy, Applications, and Challenges
Carnegie Mellon University（卡内基梅隆大学）；National University of Singapore（国立新加坡大学）；Stanford University（斯坦福大学）；University of Washington（华盛顿大学）；The University of Chicago（芝加哥大学）；Rutgers University（罗格斯大学）；Columbia University（哥伦比亚大学）；New Jersey Institute of Technology（新泽西理工学院）
Taxonomy, Evaluation and Exploitation of IPI-Centric LLM Agent Defense Frameworks
The Hong Kong University of Science and Technology（香港科技大学）；Zhejiang University of Technology（浙江工业大学）；Lingnan University（岭南大学）；School of Cyber Science and Engineering, Southeast University（东南大学计算机科学与工程学院）；ZTE Corporation（中兴通讯有限公司）
Agentic Artificial Intelligence (AI): Architectures, Taxonomies, and Evaluation of Large Language Model Agents
University College of Engineering, Anna University（安娜大学工程学院）；National Institute of Technology Tiruchirappalli（Tiruchirappalli 国家理工学院）；School of Computing and Information Systems University of Melbourne（墨尔本大学计算机与信息系统学院）
Agentic AI in Healthcare & Medicine: A Seven-Dimensional Taxonomy for Empirical Evaluation of LLM-based Agents
Department of Computer Science, New York University, CIMS, New York, USA（纽约大学计算机科学系，CIMS，纽约，美国）；Department of Computer Science, Cleveland State University, Cleveland, USA（克利夫兰州立大学计算机科学系，克利夫兰，美国）
Towards Compositional Generalization of LLMs via Skill Taxonomy Guided Data Synthesis
State Key Laboratory of Complex & Critical Software Environment, Beihang University（复杂与关键软件环境国家重点实验室，北京航空航天大学）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）；Beijing Institute of Technology（北京理工大学）；Institute of Computing Technology, CAS（中国科学院计算技术研究所）
TaxAgent: How Large Language Model Designs Fiscal Policy
Illinois Institute of Technology（伊利诺伊理工学院）；University of Texas at Austin（德克萨斯大学奥斯汀分校）；Jiangxi Normal University（江西师范大学）；Chinese University of Hong Kong（香港中文大学）
